HuggingFace Datasets
Don’t want to install HuggingFace Datasets? Drop the file here.
The first 20 minutes of any recording are transcribed free: a recording up to 20 minutes transcribes in full, a longer one is previewed, and a pack from $6 (500 minutes) transcribes the rest and opens every export, and credits never expire.
Streaming loader for Common Voice, LibriSpeech, GigaSpeech, FLEURS.
Best for training pipelines that need to stream multi-TB speech corpora without caching the whole set. Pricing: free.
What it is
The de-facto loader for every public speech dataset on the Hub. Apache-2.0.
Watch out for: Schemas vary per corpus; iterable mode lacks some indexing features.
Install / use
pip install datasetsWhat people actually do with HuggingFace Datasets-style transcription
The tool is the means. These are the jobs — each one priced at published rates, each one wired up on its own page.
Features
| Speaker diarization | No |
| Word-level timestamps | Yes |
| Streaming / real-time | No |
| Languages supported | 100 |
| HIPAA eligible | No |
Links
HuggingFace Datasets vs Whipscribe
| Feature | HuggingFace Datasets | Whipscribe |
|---|---|---|
| Category | Open source | Transcription APIs |
| Pricing | free | $6–$24 one-time packs (credits never expire) · first 20 minutes free |
| Speaker identification | No | Named in the summary, key quotes and chapters |
| Word timestamps | Yes | Yes |
| Streaming | No | No |
| Languages | 100 | 99 |
| Platforms | Linux, macOS, Windows | Web, API, MCP |
Alternatives to HuggingFace Datasets
Frequently asked about HuggingFace Datasets
Is HuggingFace Datasets free?
Yes. HuggingFace Datasets is free and open source.
Does HuggingFace Datasets work on Mac, Windows and Linux?
HuggingFace Datasets runs on Linux, macOS and Windows.
How do I install HuggingFace Datasets?
With pip: `pip install datasets`. You need Python and, for most audio tools, ffmpeg on your PATH first.
How many languages does HuggingFace Datasets support?
HuggingFace Datasets lists 100 languages. That is the Whisper-family multilingual set, so quality varies by language — English and the large European languages are strongest.
Does HuggingFace Datasets identify different speakers?
No. HuggingFace Datasets does not label speakers; a conversation comes back as one continuous text. If you need speaker labels, that is a separate tool or a different service.
Does HuggingFace Datasets give word-level timestamps?
Yes — HuggingFace Datasets produces timing per word, which is what subtitle cues and clip boundaries need.
Can HuggingFace Datasets transcribe live audio?
No — HuggingFace Datasets works on finished files, not a live stream.
Is HuggingFace Datasets HIPAA compliant?
HuggingFace Datasets does not claim HIPAA compliance. For PHI, run it on infrastructure you control or choose a service that will sign a BAA.
What are the limitations of HuggingFace Datasets?
Schemas vary per corpus; iterable mode lacks some indexing features.
Who is HuggingFace Datasets best for?
Training pipelines that need to stream multi-TB speech corpora without caching the whole set.
Does HuggingFace Datasets run offline?
HuggingFace Datasets runs on your own machine — it is open source, so nothing leaves the computer unless you configure it to.
Can I use HuggingFace Datasets in the browser?
No — HuggingFace Datasets is a Linux, macOS and Windows application, not a web app. You install it rather than sign in to it.
Where is the HuggingFace Datasets source code?
On GitHub at github.com/huggingface/datasets. It is maintained by Hugging Face.
What kind of tool is HuggingFace Datasets?
In this directory HuggingFace Datasets is filed under toolkit, data, datasets as a open-source tool.
What are the alternatives to HuggingFace Datasets?
There is a side-by-side page at /tools/hf-datasets-alternatives comparing HuggingFace Datasets with the closest tools in the same category on price, platform and features.
Whipscribe is a hosted transcription service. If you want transcripts without running infrastructure, paste a URL or drop a file in the form below — you'll have a transcript in seconds.
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One file up to 10 hours, as an upload or a link: see transcribing a long MP3 or M4A, a podcast episode as text from its link and an SRT subtitle file from any recording.
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